Engage in a thought-provoking panel discussion featuring leading experts in computer science and algorithms as they explore the concept of "Beyond Worst-Case Analysis." Moderated by Russell Impagliazzo from UCSD, the panel includes renowned researchers Ravi Kannan (Microsoft Research), Shang-Hua Teng (USC), Avrim Blum (TTIC), Santosh Vempala (Georgia Tech), and Piotr Indyk (MIT). Delve into topics such as planted clique, machine learning for algorithms, fixed stochastic models, nature of instances, ideal algorithms, NP-completeness, input complexity, sample complexity, and patterns. Gain valuable insights into the panelists' perspectives, their journey into this field, and the practical applications of beyond worst-case analysis. This 70-minute discussion, part of the Simons Institute 10th Anniversary Symposium, offers a comprehensive exploration of advanced algorithmic concepts and their implications in modern computer science.
Overview
Syllabus
Introduction
Presentation
Planted clique
Perspective
How did you get interested
Does this work
Machine Learning for Algorithms
Fixed Stochastic Model
Nature of Instances
Ideal Algorithms
NP completeness
Input complexity
Sample Complexity
Patterns
Taught by
Simons Institute